Data acquisition is the process of sampling signals that measure real world physical conditions and converting the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition systems (abbreviated with the acronym DAS or DAQ) typically convert analog waveforms into digital values for processing. The components of data acquisition systems include:
- Sensors that convert physical parameters to electrical signals.
- Signal conditioning circuitry to convert sensor signals into a form that can be converted to digital values.
- Analog-to-digital converters, which convert conditioned sensor signals to digital values.
Data acquisition begins with the physical phenomenon or physical property to be measured. Examples of this include temperature, light intensity, gas pressure, fluid flow, and force. Regardless of the type of physical property to be measured, the physical state that is to be measured must first be transformed into a unified form that can be sampled by a data acquisition system. The task of performing such transformations falls on devices called sensors.
A sensor, which is a type of transducer, is a device that converts a physical property into a corresponding electrical signal (e.g., a voltage or current) or, in many cases, into a corresponding electrical characteristic (e.g., resistance or capacitance) that can easily be converted to electrical signal.
The ability of a data acquisition system to measure differing properties depends on having sensors that are suited to detect the various properties to be measured. There are specific sensors for many different applications. DAQ systems also employ various signal conditioning techniques to adequately modify various electrical signals into voltage that can then be digitized using an Analog-to-digital converter (ADC).
Signal conditioning may be necessary if the signal from the transducer is not suitable for the DAQ hardware being used. The signal may need to be amplified, filtered or demodulated. Various other examples of signal conditioning might be bridge completion, providing current or voltage excitation to the sensor, isolation, linearization. For transmission purposes, single ended analog signals, which are more susceptible to noise can be converted to differential signals. Once digitized, the signal can be encoded to reduce and correct transmission errors.
DAQ hardware is what usually interfaces between the signal and a PC. It could be in the form of modules that can be connected to the computer's ports (parallel, serial, USB, etc.) or cards connected to slots (S-100 bus, AppleBus, ISA, MCA, PCI, PCI-E, etc.) in the motherboard. Usually the space on the back of a PCI card is too small for all the connections needed, so an external breakout box is required. The cable between this box and the PC can be expensive due to the many wires, and the required shielding.
DAQ cards often contain multiple components (multiplexer, ADC, DAC, TTL-IO, high speed timers, RAM). These are accessible via a bus by a microcontroller, which can run small programs. A controller is more flexible than a hard wired logic, yet cheaper than a CPU so that it is permissible to block it with simple polling loops. For example: Waiting for a trigger, starting the ADC, looking up the time, waiting for the ADC to finish, move value to RAM, switch multiplexer, get TTL input, let DAC proceed with voltage ramp. Many times reconfigurable logic is used to achieve high speed for specific tasks and digital signal processors are used after the data has been acquired to obtain some results. The fixed connection with the PC allows for comfortable compilation and debugging. Using an external housing a modular design with slots in a bus can grow with the needs of the user.
Not all DAQ hardware has to run permanently connected to a PC, for example intelligent stand-alone loggers and oscilloscopes, which can be operated from a PC, yet they can operate completely independent of the PC.
DAQ software is needed in order for the DAQ hardware to work with a PC. The device driver performs low-level register writes and reads on the hardware, while exposing a standard API for developing user applications. A standard API such as COMEDI allows the same user applications to run on different operating systems, e.g. a user application that runs on Windows will also run on Linux.
In 1963, IBM produced computers which were specialized for data acquisition. These include the IBM 7700 Data Acquisition System and its successor, the IBM 1800 Data Acquisition and Control System. These expensive specialized systems were surpassed in 1974 by general purpose S-100 computers and data acquisitions cards produced by Tecmar/Scientific Solutions Inc. In 1981 IBM introduced the IBM Personal Computer and Scientific Solutions introduced the first PC data acquisition products.
- Signal processing
- Data analysis
- Test method
- Input devices:
- ^ COMDEX FALL November 18, 1981 Las Vegas, NV, "Tecmar shows 20 IBM PC option cards.. LabMaster,LabTender,DADIO,DeviceTender,IEEE-488.."
- ^ PC Magazine Vol1 No.1, "Taking the Measure" by David Bunnell, "Tecmar deployed 20 option cards for the IBM PC"
- ^ PC Magazine Vol1 No.5, "Tecmar Triumph" by David Bunnell, Scientific Solutions releases 20 new products for the PC
- ^ BYTE Vol7 No.1 "Scientific Solutions - Advertisement for data acquisition boards, stepper controllers, IEEE-488 products
- ^ Test&Meausrement World Vol11 No 10 Decade of Progress Award: Scientific Solutions - LabMaster First in PC Data Acquisition
- Simon McBeath (2002). Competition Car Data Logging: A Practical Handbook. J. H. Haynes & Co.. ISBN 1-85960-653-9.
- Simon S. Young (2001). Computerized Data Acquisition and Analysis for the Life Sciences. Cambridge University Press. ISBN 0-521-56570-7.
- W. R. Leo (1994). Techniques for Nuclear and Particle Physics Experiments. Springer. ISBN 3-540-57280-5.
- Charles D. Spencer (1990). Digital Design for Computer Data Acquisition. Cambridge University Press. ISBN 0-521-37199-6.
- B.G. Thompson & A. F. Kuckes (1989). IBM-PC in the laboratory. Cambridge University Press. ISBN 0-521-32199-9.
- Buddy Fey (1996). Data Power: Using Racecar Data Acquisition. Towery Pub. ISBN 1-88109-601-7.
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